Q-omics provides the consensus-scored PLA2G4F profile across patient tissues and cancer cell-line models. PLA2G4F expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PLA2G4F is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, PLA2G4F RNA expression shows 14,403 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRP, KIRC, and BRCA as cancer lineages where PLA2G4F shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for PLA2G4F — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLA2G4F survival associations across molecular data types. PLA2G4F RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLA2G4F RNA expression–survival associations across cancer types. High PLA2G4F expression shows unfavorable associations in KIRP, SKCM, UCEC, KIRC and LIHC, but favorable associations in HNSC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for PLA2G4F RNA expression.
This table summarizes PLA2G4F tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PLA2G4F. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLA2G4F shows lower tumor expression in KIRC, KIRP, LUAD, THCA, LUSC and COAD. The KIRC box plot shows higher PLA2G4F RNA expression in normal versus tumor tissue (log2 FC = −3.987, t-test p < 0.001).
This table shows molecular features associated with PLA2G4F in patient tissues and cancer cell lines. In patient samples, PLA2G4F shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, PLA2G4F RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BREAST.
